Software Engineer AI Jobs in Austin, TX

Job Title: Software Engineer (Gen AI Solutions)

Location: Austin, TX

Duration: 14 Months + Extension

Bill Rate: $76/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description :

We need an experienced software engineer to help design, build, and optimize production LLM inference services that power GenAI features for internal and customer-facing applications. The engineer will work with our ML, platform, and product teams to make model serving faster, cheaper, and more reliable at scale.

Scope of work :

• Design, deploy, and maintain scalable inference services for open-weight and hosted LLMs on Kubernetes-based infrastructure.
• Profile and reduce end-to-end latency (time to first token, tokens per second) and cost per request.
• Apply model and serving optimizations, then benchmark the trade-offs between quality, latency, and throughput.
• Build and maintain integrations with external model APIs and internal orchestration frameworks, including routing, fallback, retries, and rate-limit handling.
• Add observability across the request path, covering logging, metrics, tracing, and dashboards for request volume, downstream call ratios, errors, and token usage.
• Set up evaluation and regression pipelines so model or serving changes don't degrade output quality.
• Do capacity planning and autoscaling, and track GPU utilization and cost.
• Write technical design docs and runbooks, and hand knowledge over to the internal team.

Expected deliverables :

• Production-ready inference service(s) with CI/CD and infrastructure as code
• Latency and cost benchmark reports, measured before and after optimization
• Monitoring dashboards and alerting
• Architecture docs, runbooks, and handover sessions

Required :

• Software engineering experience, including 2+ years on ML/LLM systems in production
• Strong Python, plus working knowledge of Go, C++, or Rust for performance-critical paths
• Hands-on experience with LLM serving frameworks: vLLM, TensorRT-LLM, TGI, SGLang, or Triton Inference Server
• Inference optimization techniques:
• Quantization (INT8/INT4, FP8, AWQ, GPTQ)
• KV-cache management, paged attention, prefix caching
• Continuous/dynamic batching and speculative decoding
• Tensor and pipeline parallelism
• Experience with PyTorch and the Hugging Face ecosystem
• Kubernetes, Docker, and GPU scheduling (NVIDIA GPU operator, node pools, autoscaling)
• Integration with hosted LLM APIs (OpenAI, Gemini, Anthropic), including streaming, retries, and rate limiting
• Observability tooling: Prometheus/Grafana, Splunk, Datadog, OpenTelemetry
• Solid grounding in distributed systems, API design (REST/gRPC), and performance profiling

Preferred :

• GenAI orchestration frameworks: Genkit, LangChain, LlamaIndex
• CUDA, Triton kernels, FlashAttention, or other low-level GPU optimization
• Model compilation and runtimes: ONNX Runtime, TorchScript/torch.compile, Core ML
• RAG pipelines and vector databases (FAISS, Milvus, pgvector)
• LLM evaluation frameworks and building automated quality and regression benchmarks
• Cost modeling and FinOps for GPU workloads
• Infrastructure as code (Terraform, Helm) and CI/CD (GitHub Actions, Jenkins)
• Contributions to open-source inference projects, or published work in ML systems

Soft skills :

• Can turn ambiguous requirements into concrete technical plans and trade-off proposals
• Communicates clearly in writing (design docs, benchmark reports)
• Works well with cross-functional teams of engineers and PMs.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.